The information content of turbine engine data - A chance for recording-based life usage monitoring

The most important input signals for calculating the life consumption of fracture critical parts of turbine engines were analyzed for their information content. This information content determines the data volume to be transmitted and stored, if instead of calculating life usage in real-time in the on-board monitoring system this calculation is postponed to later processing in a ground-based support system. Signals from various sources are shown and processes contributing to an increase in information theoretic entropy are identified. Some methods to avoid unnecessary components of the composition of signals are proposed. It is shown that a considerable part of the entropy determining the storage requirements can be either avoided or removed, if only that part of the information is retained that has a deterministic influence on the results of a variety of algorithms for life usage monitoring. If proper rate conversion, quantization, low pass filtering and noise suppression is applied, highly efficient methods for data compression based on delta coding, statistical adaptive prediction models and arithmetic coders can be used to reduce the data volume to astonishingly low figures. On-board storage of 100 hours of engine operation and archiving the complete running history in the ground support system could remove many of the shortcomings of existing LUM systems.